hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Intelligent vocal cord image analysis for categorizing laryngeal diseases
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Lithuania.
Kaunas University of Technology, Lithuania.
Kaunas University of Medicine, Kaunas, Lithuania.
2005 (English)In: Innovations in applied artificial intelligence / [ed] Moonis Ali, Floriana Esposito, Springer, 2005, p. 69-78Conference paper, Published paper (Refereed)
Abstract [en]

Colour, shape, geometry, contrast, irregularity and roughness of the visual appearance of vocal cords are the main visual features used by a physician to diagnose laryngeal diseases. This type of examination is rather subjective and to a great extent depends on physician’s experience. A decision support system for automated analysis of vocal cord images, created exploiting numerous vocal cord images can be a valuable tool enabling increased reliability of the analysis, and decreased intra- and inter-observer variability. This paper is concerned with such a system for analysis of vocal cord images. Colour, texture, and geometrical features are used to extract relevant information. A committee of artificial neural networks is then employed for performing the categorization of vocal cord images into healthy, diffuse, and nodular classes. A correct classification rate of over 93% was obtained when testing the system on 785 vocal cord images.

Place, publisher, year, edition, pages
Springer, 2005. p. 69-78
Series
Lecture notes in computer science, ISSN 0302-9743 ; 3533
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-3325DOI: 10.1007/11504894_11ISI: 000230355800011Scopus ID: 2-s2.0-26944490684ISBN: 978-354026551-1 OAI: oai:DiVA.org:hh-3325DiVA, id: diva2:300233
Conference
18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 2005
Available from: 2010-02-25 Created: 2009-12-01 Last updated: 2018-01-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Verikas, Antanas

Search in DiVA

By author/editor
Verikas, Antanas
By organisation
Halmstad Embedded and Intelligent Systems Research (EIS)
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 148 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf